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Record W4389037369 · doi:10.1080/23311975.2023.2284814

Four decades of counterfeit research: A bibliometric analysis

2023· article· en· W4389037369 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCogent Business & Management · 2023
Typearticle
Languageen
FieldMedicine
TopicPharmaceutical Quality and Counterfeiting
Canadian institutionsToronto Metropolitan University
FundersSultan Qaboos University
KeywordsCounterfeitRigourSystematic reviewScopusBibliometricsSubject (documents)CredibilityTransparency (behavior)NarrativeSociologyLibrary scienceSocial scienceData scienceComputer sciencePolitical scienceMEDLINE

Abstract

fetched live from OpenAlex

This paper assesses the evolution of last 43 years in counterfeit research with respect to sources of knowledge (i.e.journals, authors, institutions, countries) and research themes.The oldest paper on this subject discovered in the Scopus database was published 43 years ago, yet a time frame was not specified.Sources of knowledge are assessed on research productivity (quantitative) as well as impact (qualitative).Research themes, key areas of focus within the counterfeit research landscape, are identified and discussed to conceptualize our understanding of the field.Via a systematic literature review, 713 peer-reviewed academic articles published in 282 journals from 1978 to 2021 were selected as the sample for this study.The systematic review technique was chosen as compared with narrative reviews of the literature it focuses on open, extensive, and detailed approaches to literature searches, in addition to conforming to the scientific criteria utilised in primary research, namely transparency, rigour, comprehensiveness, and reproducibility.A database of references and citations was created for analysis.The data was analyzed to prepare comparative tables.Further, the Leximancer software was used to generate lexical conceptual trends.This data was further analyzed to identify emerging themes.The Journal of Business Ethics had the highest number of articles and citations, followed by the Journal of Business Research and Business Horizons.Ian Phau (14 articles) and Michael D. Smith, (9 articles) were the most prolific authors.Joseph Nunes and Ian Phau attained the highest number of citations, cited 658 and 577 times respectively.Eight major research themes were identified: products, piracy, model, price, firms, digital, supply, and ethical.Each theme was analyzed over time.The major research areas analyzed across the articles over time were Technology (particularly "Technology" and "Software" topics) and Ethics (particularly "IP" and "Legislation").The identification of these research area captures the essence of the paper's uniqueness and contribution to this field of research.This is the first systematic literature review in counterfeit literature that captures multi-decade sources of knowledge in business journals.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesBibliometrics
Consensus categoriesBibliometrics
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.748
Threshold uncertainty score0.940

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0710.319
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.403
GPT teacher head0.486
Teacher spread0.084 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it